Stefan Hey

The association between short periods of everyday life activities and affective states : a replication study using ambulatory assessment

Regularly conducted exercise programs effectively influence affective states. Studies suggest that this is also true for short bouts of physical activity (PA) of 10 min or less. Accordingly, everyday life activities of short duration might be used to regulate affective states. However, this association has rarely been studied in reference to unstructured activities in ongoing real-life situations. The current study examined the influence of various everyday life activities on three dimensions of mood (valence, calmness, energetic arousal) in a predominantly inactive sample. Ambulatory Assessment (AA) was used to investigate the association between actual PA and affective states during the course of 1 day. Seventy-seven students ages 19–30 participated in the study. PA was assessed with accelerometers, and affective state assessments were conducted hourly using an e-diary with a six-item mood scale that was specially designed for AA. Multilevel analyses indicated that the mood dimensions energetic arousal (p = 0.001) and valence (p = 0.005) were positively influenced by the intensity of the activity carried out in the 10-min prior to the assessment. As their activity increased, the participants’ positive feelings and energetic arousal increased. However, the students’ calmness was not affected by their activity levels. The findings highlight the importance of integrating short activity intervals of 10 min or less into everyday life routines to improve affective states.

Home-based system for physical activity monitoring in patients with multiple sclerosis (Pilot study)

BackgroundLimitations in physical activity are considered as a key problem in patients with multiple sclerosis (PwMS). Contemporary methods to assess the level of physical activity in PwMS are regular clinical observation. However, these methods either rely on high recall and accurate reporting from the patients (e.g. self-report questionnaires), or they are conducted during a particular clinical assessment with predefined activities. Therefore, the main aim of this pilot study was to develop an objective method to gather information about the real type and intensity of daily activities performed by PwMS in every-day living situations using an accelerometer. Furthermore, the accelerometer-derived measures are investigated regarding their potential for discriminating between different MS groups.MethodsEleven PwMS that were able to walk independently (EDSS ≤ 5) were divided into two groups: mild disability (EDSS 1–2.5; n = 6) and moderate disability (EDSS 3 –5; n = 5). Participants made use of an activity monitor device attached to their waist during their normal daily activities over 4 measurements. Activity parameters were assessed and compared for the time of each participant’s first measurement and follow-up measurement. Furthermore, differences between both subgroups, and the correlation of activity parameters with the clinical neurological variable (EDSS) were investigated.ResultsParticipants showed significant decline in step count (p = 0.008), maximum walking speed (p = 0.02) and physical activity intensity (p = 0.03) throughout the study period. Compared to the mild subgroup, moderate affected participant accumulated less number of steps (G1: 9214.33 ± 2439.11, G2: 5018.13 ± 2416.96; p < 0.005) and were slower (G1: 1.48 ± 0.19, G2: 1.12 ± 0.44; p = 0.03). Additionally, the EDSS correlated negatively with mean walking speed (r = - 0.71, p = 0.01) and steps count (r = - 0.54, p = 0.08).ConclusionsIn this study, we used a portable activity monitoring sensor to gather information about everyday physical activity in PwMS at home. We showed that objective measurements using simple 3D accelerometers can track daily physical activity fluctuation. Furthermore, they track disability changes better than clinical measures. Thus, they can help to develop activity based treatments for PwMS.

Classification of human physical activity and energy expenditure estimation by accelerometry and barometry

Regular exercise and physical activity are among the most important factors influencing the quality of life and make a significant contribution to the maintenance of health and well-being. The assessment of physical activity via accelerometry has become a promising technique often used as means to objectively measure physical activity. This work proposes a simple and reliable method to assess human physical activity and calculate the energy expenditure (EE) by using an acceleration and an air pressure sensor. Our proposed algorithm differentiates between 7 activities with an average accuracy of 98.2% and estimates the second by second EE with an average percent error of 1.59 ± 8.20% using a single measurement unit attached to the subjects hip.

Characteristics of the activity-affect association in inactive people: an ambulatory assessment study in daily life.

Acute and regular exercise as well as physical activity (PA) is related to well-being and positive affect. Recent studies have shown that even daily, unstructured physical activities increase positive affect. However, the attempt to achieve adherence to PA or exercise in inactive people through public health interventions has often been unsuccessful. Most studies analyzing the activity-affect association in daily life, did not report participants’ habitual activity behavior. Thus, samples included active and inactive people, but they did not necessarily exhibit the same affective reactions to PA in daily life. Therefore the present study investigated whether the association between PA and subsequent affective state in daily life can also be observed in inactive individuals. We conducted a pilot study with 29 inactive university students (mean age 21.3 ± 1.7 years) using the method of ambulatory assessment. Affect was assessed via electronic diary and PA was measured with accelerometers. Participants had to rate affect every 2 h on a six item bipolar scale reflecting the three basic mood dimensions energetic arousal, valence, and calmness. We calculated activity intensity level [mean Metabolic Equivalent (MET) value] and the amount of time spent in light activity over the last 15 min before every diary prompt and conducted within-subject correlations. We did not find significant associations between activity intensity and the three mood dimensions. Due to the high variability in within-subject correlations we conclude that not all inactive people show the same affective reactions to PA in daily life. Analyzing the PA-affect association of inactive people was difficult due to little variance and distribution of the assessed variables. Interactive assessment and randomized controlled trials might help solving these problems. Future studies should examine characteristics of affective responses of inactive people to PA in daily life. General assumptions considering the relation between affect and PA might not be suitable for this target group.

Continuous Noninvasive Pulse Transit Time Measurement for Psycho-physiological Stress Monitoring

Stress is one of the most common reasons for a number of serious diseases. For the prevention and treatment of stress, a psycho-physiological monitoring system for stress measurement is needed. Because of the multifarious influences of stress on the physiological response of the body, a stress measurement system has to take into account as many parameters as possible. The pulse transit time (PTT), which is determined by measuring the ECG and the pulse wave at for example a finger, gives comprehensive information about the cardiovascular system. In a study we investigate the correlation between the PTT and the stress induced by a psychological experiment. We found out that there is a strong correlation and that PTT is an appropriate parameter for stress measurement.

System for Body and Mind Monitoring in coaching process

In order to investigate the correlation between stress and cognitive performance, a mobile Body & Mind Monitoring System was implemented. This system has a modular design and contains different modules allowing a long time and noninvasive monitoring of physiological parameters of a test person in his every day life, for instance ECG, GSR, PPG, respiration and physical activity. The functionality of the created set-up was validated and clinical studies can now be conducted.

Noncontact measurement of intraocular pressure using a modified Michelson interferometer

This paper describes a new method to examine the intraocular pressure (IOP) without any contact with the eye. In our new approach the IOP is determined indirectly from the acoustic properties of the eye, as the resonance frequencies of the bulbus are shifting with increasing IOP. In a first step simulations were made with the Finite Element Method to explore the correlation between the IOP and the acoustic properties of the bulbus. The results showed a significant rise of the resonance-frequencies with increasing IOP. Simultaneously a in-vitro measurement system was built comprising a modified michelson interferometer to measure the vibrations, a transducer to stimulate the eye and a controlling PC. With this system measurements were made with artificial eyes and enucleated pig eyes to prove the correlation experimentally. The eyes were stimulated both contacting the eye with a transducer by a stick and contactless with sonic waves. Several series of measurements showed a proportional constant of 1,25 Hz/mmHg in average, which can be detected easily. The standard deviation measuring different pig eyes was 4,5 mmHg. Next a in-vivo system was developed to study the acoustic behavior of the human eye in the real environment. The in-vivo system consists of a miniaturized semiconductor-laser interferometer complying laser safety requirements, an automatic positioning unit and an excitation unit to stimulate vibrations of the eye. Sub-micrometer vibrations of the eye can be measured in-vivo with this system.

Mobile Multi-parametric Sensor System for Diagnosis of Epilepsy and Brain Related Disorders

Epilepsy is the commonest serious brain disorder, affecting 1-2% of the general population. Epileptic seizures are usually expressed with a wide range of paroxysmal recurring motor, cognitive, autonomic symptoms and EEG changes. Therefore reliable diagnosis requires state of the art monitoring and communication technologies providing real-time, accurate and continuous brain and body multi-parametric data measurements. The purpose of this paper is to present an adequate mobile system comprising all required sensor types for the everyday life monitoring of patients with epilepsy.

Synchronization in wireless biomedical-sensor networks with Bluetooth Low Energy

Abstract Bluetooth Low Energy (BLE) has reduced the energy consumption for sensor nodes drastically. One major reason for this improvement is a non-continuous connection between the nodes. But this causes also a nondeterministic data transmission time. Most synchronization protocols are influenced by this characteristic, with the result of less accuracy. In wireless body sensor networks this accuracy is often of vital importance. Therefore this paper evaluates different synchronization principles customized for BLE. For the evaluation measurements we used two BLE modules connected to one micro controller. This setup allowed us to calculate the error directly for the different principles. First we measured the send-receive time as a reference which influences most synchronization protocols. This time is directly affected by random transmission delays of BLE. Second we used the time difference between receiving and acknowledging a message as principle (A). The last principle (B) can only be used between nodes that use BLE that don’t require a constant connection, because it needs to connect and disconnect the nodes. After a new connection the “connected” events occur in the BLE nodes almost at the same time and can be used for synchronization. The reference measurement showed the worst results. The average delay was 4.76 ms with a standard deviation of 2.32 ms. Principle (A) showed average delays of 7.51 ms, which was almost exactly 1 connection interval in our setup. The standard deviation was 0.41 ms. Principle (B) showed the best results with an average time difference of 39.92 μs and a standard deviation of 14.19 μs The results showed that with the principles (A) and (B) the synchronization of nodes can be highly improved compared to the reference. In future we will test the principles with synchronization protocols in real sensor nodes also with respect to the processor load.

Mobile monitoring of epileptic patients using a reconfigurable cyberphysical system that handles multi-parametric data acquisition and analysis

Epilepsy is one of the commonest, serious and divesting brain disorders. Although it is still an incurable disorder in most cases its symptoms can be ameliorated by lifelong pharmaceutical treatment. Depending on the type of epilepsy and due to its multifactorial causes, different brain and body parameters need to be assessed continuously over a long period. This allows clinicians to have a better understanding of the patients state of health and to be able to continuously adjust and change the medical treatment accordingly. Beside this, multi-parametric monitoring could be used for other purposes such as accurate diagnosis, detection of seizures, alerting and prevention and presurgical evaluation. The purpose of this paper is to present the architecture of the whole cyberphysical system, comprising a modular framework that is able to connect all the required sensor types and perform online data analysis for the monitoring of patients with epilepsy.